Zhang Xueliang, Nie Yan, Li Dan, Zhou Chunhua
Department of Pharmacy, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Department of Pharmacy, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Front Pharmacol. 2024 Dec 12;15:1503059. doi: 10.3389/fphar.2024.1503059. eCollection 2024.
This study compares the relationships between five anthropometric indices, a body shape index (ABSI), body roundness index (BRI), waist circumference (WC), body mass index (BMI) and waist-to-height ratio (WHtR), and hypertension, assessing their predictive capacities. The aim is to determine the specific numerical changes in hypertension incidence, systolic blood pressure (SBP) and diastolic blood pressure (DBP) for each increase in standard deviation of these indices, and to identify the optimal predictive indicators for different populations, including the calculation of cutoff values.
This study used data from the NHANES datasets spanning 2007 to 2018. Logistic regression analysis was used to quantify the associations between these anthropometric indices and hypertension, calculating β coefficients and odds ratios (ORs). Receiver operating characteristic (ROC) analysis was used to evaluate the predictive ability of each index for hypertension.
For each increase in standard deviation in WC, BMI, WHtR, ABSI and BRI, the prevalence of hypertension increased by 33% (95% CI: 27%-40%), 32% (95% CI: 26%-38%), 35% (95% CI: 28%-42%), 9% (95% CI: 4%-16%) and 32% (95% CI: 26%-38%), respectively. The SBP correspondingly increased by 2.36 mmHg (95% CI: 2.16-2.56), 2.41 mmHg (95% CI: 2.21-2.60), 2.48 mmHg (95% CI: 2.28-2.68), 0.42 mmHg (95% CI: 0.19-0.66) and 2.46 mmHg (95% CI: 2.26-2.66), respectively. Similarly, DBP increased by 1.83 mmHg (95% CI: 1.68-1.98), 1.72 mmHg (95% CI: 1.58-1.87), 1.72 mmHg (95% CI: 1.57-1.88), 0.44 mmHg (95% CI: 0.27-0.62) and 1.64 mmHg (95% CI: 1.48-1.79). In the youth and middle-aged groups, WC had the best predictive ability, with AUCs of 0.749 and 0.603, respectively. Among the elderly group, the AUCs for all five indices ranged between 0.5 and 0.52.
Increases in WC, BMI, WHtR and BRI are significantly associated with higher incidences of hypertension and increases in SBP and DBP, while the impact of ABSI on blood pressure is relatively weak. Stratified analysis indicates significant age-related differences in the predictive value of these indices, with the strongest associations observed in the youth group, followed by the middle age group, and the weakest in the elderly. WC demonstrates excellent predictive ability across youth populations.
本研究比较了五个身体测量指标,即体型指数(ABSI)、身体圆润度指数(BRI)、腰围(WC)、体重指数(BMI)和腰高比(WHtR)与高血压之间的关系,评估它们的预测能力。目的是确定这些指标每增加一个标准差时高血压发病率、收缩压(SBP)和舒张压(DBP)的具体数值变化,并为不同人群确定最佳预测指标,包括计算临界值。
本研究使用了2007年至2018年美国国家健康与营养检查调查(NHANES)数据集的数据。采用逻辑回归分析来量化这些身体测量指标与高血压之间的关联,计算β系数和比值比(OR)。采用受试者工作特征(ROC)分析来评估每个指标对高血压的预测能力。
WC、BMI、WHtR、ABSI和BRI每增加一个标准差,高血压患病率分别增加33%(95%CI:27%-40%)、32%(95%CI:26%-38%)、35%(95%CI:28%-42%)、9%(95%CI:4%-16%)和32%(95%CI:26%-38%)。SBP相应分别增加2.36 mmHg(95%CI:2.16-2.56)、2.41 mmHg(95%CI:2.21-2.60)、2.48 mmHg(95%CI:2.28-2.68)、0.42 mmHg(95%CI:0.19-0.66)和2.46 mmHg(95%CI:2.26-2.66)。同样,DBP分别增加1.83 mmHg(95%CI:1.68-1.98)、1.72 mmHg(95%CI:1.58-1.87)、1.72 mmHg(95%CI:1.57-1.88)、0.44 mmHg(95%CI:0.27-0.62)和1.64 mmHg(95%CI:1.48-1.79)。在青年和中年组中,WC具有最佳预测能力,AUC分别为0.749和0.603。在老年组中,所有五个指标的AUC在0.5至0.52之间。
WC、BMI、WHtR和BRI的增加与高血压发病率升高以及SBP和DBP升高显著相关,而ABSI对血压的影响相对较弱。分层分析表明,这些指标的预测价值存在显著的年龄相关差异,在青年组中关联最强,其次是中年组,在老年组中最弱。WC在青年人群中表现出出色的预测能力。